The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
Machine learning systems typically utilize a large amount of data organized into features to assist in the generation and adaption of a prediction model. As the number of features increases, the associated model becomes more complex. For prediction events that include only a small number of features typical prediction models may provide inaccurate or otherwise unacceptable prediction results.
The present disclosure provides for the generation, adaptation and utilization of a prediction model to obtain improved performance, for example, in determining prediction results based on prediction events irrespective of the number of features associated therewith.